Stochastic model predictive control approaches applied to drinking water networks
Summary Control of drinking water networks is an arduous task, given their size and the presence of uncertainty in water demand. It is necessary to impose different constraints for ensuring a reliable water supply in the most economic and safe ways. To cope with uncertainty in system disturbances du...
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| Vydané v: | Optimal control applications & methods Ročník 38; číslo 4; s. 541 - 558 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article Publikácia |
| Jazyk: | English |
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Glasgow
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01.07.2017
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| ISSN: | 0143-2087, 1099-1514 |
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| Abstract | Summary
Control of drinking water networks is an arduous task, given their size and the presence of uncertainty in water demand. It is necessary to impose different constraints for ensuring a reliable water supply in the most economic and safe ways. To cope with uncertainty in system disturbances due to the stochastic water demand/consumption and optimize operational costs, this paper proposes three stochastic model predictive control (MPC) approaches, namely, chance‐constrained MPC, tree‐based MPC, and multiple‐scenario MPC. A comparative assessment of these approaches is performed when they are applied to real case studies, specifically, a sector and an aggregate version of the Barcelona drinking water network in Spain. Copyright © 2016 John Wiley & Sons, Ltd. |
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| AbstractList | Summary Control of drinking water networks is an arduous task, given their size and the presence of uncertainty in water demand. It is necessary to impose different constraints for ensuring a reliable water supply in the most economic and safe ways. To cope with uncertainty in system disturbances due to the stochastic water demand/consumption and optimize operational costs, this paper proposes three stochastic model predictive control (MPC) approaches, namely, chance-constrained MPC, tree-based MPC, and multiple-scenario MPC. A comparative assessment of these approaches is performed when they are applied to real case studies, specifically, a sector and an aggregate version of the Barcelona drinking water network in Spain. Copyright © 2016 John Wiley & Sons, Ltd. Summary Control of drinking water networks is an arduous task, given their size and the presence of uncertainty in water demand. It is necessary to impose different constraints for ensuring a reliable water supply in the most economic and safe ways. To cope with uncertainty in system disturbances due to the stochastic water demand/consumption and optimize operational costs, this paper proposes three stochastic model predictive control (MPC) approaches, namely, chance‐constrained MPC, tree‐based MPC, and multiple‐scenario MPC. A comparative assessment of these approaches is performed when they are applied to real case studies, specifically, a sector and an aggregate version of the Barcelona drinking water network in Spain. Copyright © 2016 John Wiley & Sons, Ltd. Control of drinking water networks is an arduous task, given their size and the presence of uncertainty in water demand. It is necessary to impose different constraints for ensuring a reliable water supply in the most economic and safe ways. To cope with uncertainty in system disturbances due to the stochastic water demand/consumption and optimize operational costs, this paper proposes three stochastic model predictive control (MPC) approaches, namely, chance-constrained MPC, tree-based MPC, and multiple-scenario MPC. A comparative assessment of these approaches is performed when they are applied to real case studies, specifically, a sector and an aggregate version of the Barcelona drinking water network in Spain. Peer Reviewed |
| Author | Maestre, José M. Velarde, Pablo Puig, Vicenç Ocampo‐Martinez, Carlos Grosso, Juan M. |
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| Contributor | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control |
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| Copyright | Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd. An error occurred on the license name. info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-nd/3.0/es |
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Control of drinking water networks is an arduous task, given their size and the presence of uncertainty in water demand. It is necessary to impose... Summary Control of drinking water networks is an arduous task, given their size and the presence of uncertainty in water demand. It is necessary to impose... Control of drinking water networks is an arduous task, given their size and the presence of uncertainty in water demand. It is necessary to impose different... |
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| SubjectTerms | Automàtica i control Classificació INSPEC Control theory Demand (economics) Drinking water Informàtica management of water systems Mathematical models model predictive control Predictive control Probability theory Stochastic models stochastic programming system disturbances Uncertainty Water supply Water supply systems Àrees temàtiques de la UPC |
| Title | Stochastic model predictive control approaches applied to drinking water networks |
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